Field of the Invention
Exemplary embodiments of the present invention relate to an image processing method of a vehicle camera and an image processing apparatus using the same, and more particularly, to an image processing method of a vehicle camera and an image processing apparatus using the same, which are capable of improving the stability and reliability of a vehicle driving assist system that uses a night image captured by a camera mounted on a vehicle by effectively correcting the night image.
Description of the Related Art
Recently, a detection device for detecting objects, such as traffic lanes, signs, vehicles, or other geographic features, using an optical device, such as a camera mounted on a vehicle, is actively developed. Information about an object detected by such a detection device may be used for safety driving of a vehicle. However, while a vehicle is driven, a pitch motion may be generated depending on the state of a road surface on a road. The pitch motion denotes the up-down movement of a vehicle attributable to moving road conditions.
Such a pitch motion in the vehicle may become a cause of generating an error when the detection device detects the object. Accordingly, there is a need for a technology capable of minimizing an error in the pitch motion.
In the case of an image stabilization method, such as an existing pitch motion solution, edge components near the horizon that appear in an image are extracted, a difference between an image of a previous frame and an image of a current frame is measured, and a current pitch motion of a vehicle is estimated based on a result of the difference. An example related to such pitch motion estimation is disclosed in Korean Patent Application Publication No. 2013-0015974 (Feb. 14, 2013).
However, there is a case where the horizon is unable to be monitored using a camera because intensity of illumination is insufficient at night. In such a case, performance may be deteriorated if the existing method is used.
In relation to a streetlamp appearing at the upper end of an image at night, the most important thing is to analyze a motion within then image of the streetlamp when the motion characteristic of the streetlamp are searched for using data, such as a motion within an image, vehicle speed, and a yaw rate. In this case, the motion within then image of the streetlamp is chiefly analyzed using a tracking algorithm.
If many light sources are present in front of the vehicle in various forms, however, a computational load required to perform the tracking algorithm is very great. As a result, there is a problem in that performance is deteriorated.